Purpose -The purpose of this study is to investigate empirically the relationship between intellectual capital and financial performance of 65 Indian banks for a period of ten years from 1999 to 2008. Design/methodology/approach -Reserve Bank of India's database and Annual reports, especially the profit and loss accounts and balance sheets of the banks for the relevant years have been used to obtain the data. Value added intellectual coefficient (VAICt) method is applied for measuring the value based performance of banks. Return on assets (ROA) and return on equity (ROE) are used to measure the profitability and productivity of Indian banks, measured by assets turnover ratio (ATO). The intellectual capital (human capital and structural capital) and physical capital of selected banks have been analyzed and their impact on corporate performance has been measured using multiple regression technique. Findings -The analysis indicates that the relationships between the performance of a bank's intellectual capital, and financial performance indicators, namely profitability and productivity, are varied. The study results suggest that banks' intellectual capital is vital for their competitive advantage.Research limitations/implications -The study uses only 65 leading Indian banks, including foreign banks operating in India. The value added intellectual coefficient (VAICt), introduced by Pulic, is used in this study as a basic methodology to measure the IC performance of banks. Practical implications -The VAICt method can be used as an important tool by the decision makers in the knowledge economy to integrate the intellectual capital in the decision making process. Originality/value -This is one of the first empirical researches in India that examines the impact of IC on financial performance of the Indian banking sector in the long term.

Purpose -This paper seeks to estimate and analyze the relationship between intellectual capital and corporate conventional financial performance measures of Indian software and pharmaceutical companies for a period of five years from 2002 to 2006. Design/methodology/approach -Annual reports, especially the profit and loss accounts and balance sheets of the selected companies for the relevant years have been used to obtain the data. International literatures on intellectual capital with specific reference to measurement tools and techniques have been reviewed. Value Added Intellectual Coefficient TM (VAIC) method is applied for measuring the value based performance of the companies. Corporate conventional performance financial measures used in this analysis are: profitability; productivity; and market valuation. It is an empirical study using multiple regression analysis for the data analysis. The intellectual capital (human capital and structural capital) and physical capital of the arbitrarily selected companies have been analyzed and their impact on corporate performance has been measured using multiple regression technique. Findings -The analysis indicates that the relationships between the performance of a company's intellectual capital and conventional performance indicators, namely, profitability, productivity and market valuation, are varied. The findings suggest that the performance of a company's intellectual capital can explain profitability but not productivity and market valuation in India.Research limitations/implications -The study has been conducted on a small sample of 80 companies belonging to the India software and pharmaceutical sectors. For a better understanding, a larger data set covering all prominent industry segments will be helpful. Practical implications -Intellectual capital is an area of interest to numerous parties, e.g. shareholders, managers, policy makers, institutional investors. This paper throws some light on the new performance indicator, which Indian managers can use in order to evaluate the corporate performance and benchmark it with global standards. This is useful particularly in the context of the "knowledge economic" environment. Originality/value -The paper represents a pioneering attempt to understand the implications of the business performance of the Indian software and pharmaceutical sectors from an intellectual resource perspective.

This study investigates the association between firm characteristics, corporate governance attributes and the level of corporate disclosure of listed firms in India. The research paper has been based on a sample of 60 firms listed in the Bombay Stock Exchange (BSE) / National Stock Exchange (NSE) during the study period from 2000-01 to 2009-10. The study has used the Standard & Poor (2008) model for measuring the level of corporate disclosure. To examine the association between explanatory variables and the level of corporate disclosure, multiple regression model has been used. The results suggest a positive relationship between board size, ratio of audit committee members to total board members, family control, CEO duality, firm size, profitability, liquidity and the extent of corporate disclosure. However, the degree of corporate disclosure is negatively related to board composition, leverage and age of the firm.

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<abstract><p>Production of defective products is a very general phenomenon. But backorder and shortages occur due to this defective product, and it hampers the manufacturer's reputation along with customer satisfaction. That is why, these outsourced products supply, a portion of required products for in-line production. This study develops a flexible production model that reworks repairable defective products and outsources products to prevent backlogging. A percentage of total in-line production is defective products, which is random, and those defective products are repairable. A green investment helps the reworking process, which has a direct impact on the market demand for products. A classical optimization solves the profit maximization model, and a numerical method proves the global optimal solutions. Sensitivity analysis, managerial insights, and discussions provide the highlights and decision-making strategies for the applicability of this model.</p></abstract>